Triple
T34167007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La France pears |
E876438
|
entity |
| Predicate | comparedToAsianPears |
P51217
|
FINISHED |
| Object | softer texture |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: softer texture | Statement: [La France pears, comparedToAsianPears, softer texture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: comparedToAsianPears Context triple: [La France pears, comparedToAsianPears, softer texture]
-
A.
comparisonWithAsianRice
Indicates a relationship in which something is compared or contrasted specifically with Asian rice in terms of some property or characteristic.
-
B.
comparisonAspect
chosen
Indicates that two or more entities are being compared specifically with respect to a particular shared attribute or dimension.
-
C.
isComparedTo
Indicates that one entity is evaluated or measured in relation to another to highlight similarities, differences, or relative qualities.
-
D.
tasteComparedTo
Indicates a comparison of the taste or flavor of one entity relative to another.
-
E.
relativeFruitSize
Indicates the comparative size relationship between one fruit and another (e.g., larger than, smaller than, or similar in size).
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd32848ea88190a71e6df402bbb30e |
completed | May 8, 2026, 12:47 a.m. |
| PD | Predicate disambiguation | batch_69fd2d7e95588190991d5f21e25155df |
completed | May 8, 2026, 12:25 a.m. |
Created at: May 1, 2026, 1:54 a.m.